Heredity (2020) 125:396–416 https://doi.org/10.1038/s41437-020-0336-6 REVIEW ARTICLE Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding 1 1 2,3 4 5 Michael F. Scott ● Olufunmilayo Ladejobi ● Samer Amer ● Alison R. Bentley ● Jay Biernaskie ● 6 7 8 9 10 4 Scott A. Boden ● Matt Clark ● Matteo Dell’Acqua ● Laura E. Dixon ● Carla V. Filippi ● Nick Fradgley ● 4 11 2 4 12 Keith A. Gardner ● Ian J. Mackay ● Donal O’Sullivan ● Lawrence Percival-Alwyn ● Manish Roorkiwal ● 13 12 12 7 14 Rakesh Kumar Singh ● Mahendar Thudi ● Rajeev Kumar Varshney ● Luca Venturini ● Alex Whan ● 4 1 James Cockram ● Richard Mott Received: 27 January 2020 / Revised: 16 June 2020 / Accepted: 16 June 2020 / Published online: 3 July 2020 © The Author(s) 2020. This article is published with open access Abstract Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For 1234567890();,: 1234567890();,: example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm ‘package’ that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding. Over recent years, numerous multi-parent populations (MPPs) These authors contributed equally: James Cockram, Richard Mott have been successfully developed in crops (Huang et al. 2015; These authors have joined first authorship: Michael F. Scott, Cockram and Mackay 2018). MPPs bring together key Olufunmilayo Ladejobi genomic, phenotypic and germplasm resources to form a Guest editor: Lindsey Compton * Michael F. Scott 7 Natural History Museum, London, UK [email protected] 8 Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy * Olufunmilayo Ladejobi 9 [email protected] Faculty of Biological Sciences, University of Leeds, Leeds LS2 9JT, UK 10 1 UCL Genetics Institute, Gower Street, London WC1E 6BT, UK Instituto de Agrobiotecnología y Biología Molecular (IABIMO), INTA-CONICET, Nicolas Repetto y Los Reseros s/n, 1686 2 University of Reading, Reading RG6 6AH, UK Hurlingham, Buenos Aires, Argentina 3 Faculty of Agriculture, Alexandria University, Alexandria 23714, 11 SRUC, West Mains Road, Kings Buildings, Edinburgh EH9 3JG, Egypt UK 4 The John Bingham Laboratory, NIAB, 93 Lawrence Weaver 12 Center of Excellence in Genomics and Systems Biology, Road, Cambridge CB3 0LE, UK International Crops Research Institute for the Semi-Arid Tropics 5 Department of Plant Sciences, University of Oxford, South Parks (ICRISAT), Hyderabad, India Road, Oxford OX1 3RB, UK 13 International Center for Biosaline Agriculture, Academic City, 6 School of Agriculture, Food and Wine, University of Adelaide, Dubai, United Arab Emirates Glen Osmond, SA 5064, Australia 14 CSIRO, GPO Box 1700, Canberra, ACT 2601, Australia Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding 397 platform for research and development. In this review, we precision (Dudley 1993; Darvasi and Soller 1995). Despite examine three themes covering new developments in crop its potential benefits, AIC has seldom been used in crops. MPP research: (1) we survey the rapidly expanding variety of So far, examples of AIC exist in two plant species, thale crop MPPs, explaining how differences in their design and cress (Arabidopsis thaliana, Gerald et al. 2014) and maize construction affect their power and precision in mapping (Zea mays, Lee et al. 2002; Balint-Kurti et al. 2010), dis- quantitative trait loci (QTL), on which we provide a brief cussed further by Cockram and Mackay (2018). A possible primer. (2) We review the use of genomic technologies in reason for the lack of uptake, acknowledged by Darvasi and MPPs, which have proven particularly suitable for gathering Soller (1995), is that simply increasing population size in dense genomic information across large populations. We bi-parental populations also increases mapping precision. make general recommendations for collecting genotypic Although large bi-parental populations also require resources in MPPs. (3) We discuss successful applications of increased phenotyping and genotyping, there is no MPPs, particularly where they have been used for breeding requirement for additional crossing to create the population, and pre-breeding. This includes the identification of QTL, the which is particularly important for selfing species where application of genomic prediction to MPPs, and the direct use manual crossing is onerous. of MPP lines as germplasm for varietal release or pre- Currently, the two most popular MPP designs in plants breeding. These recent developments have shown the poten- are nested association mapping (NAM) and multi-parent tial of MPPs for crop improvement. advanced generation inter-cross (MAGIC) populations. NAM population construction involves a series of crosses between a recurrent founder line and a number of alternative Multi-parent populations (MPPs) founders (Fig. 1). NAMs can be thought of as sets of bi- parental populations all linked by a common parent. They Bi-parental populations, derived from crosses between two are therefore conceptually familiar for those used to work- inbred lines, have been the standard design for genetic ing with bi-parental populations. While NAM captures mapping in crops. There are three key advantages to bi- additional genetic diversity, increased genetic recombina- parental populations: (1) the relative simplicity of their tion is essentially only captured via increasing the numbers construction. Just two generations are needed for F2 (selfed/ of lines screened—as is the case in bi-parental populations. inter-crossed F1 hybrids) populations, and only about six In contrast, the MAGIC design is more complex. MAGIC is further generations of inbreeding in self-fertilising species an extension of AIC in some respects, except several are needed to make recombinant inbred lines (RILs) whose founders are inter-crossed over multiple generations before genomes are fixed. (2) Their high power to detect QTL selfing to generate inbred lines. MAGIC populations typi- because all allele frequencies are typically close to the cally descend from 4, 8 or 16 parents, consistent with a optimal value of 50%. (3) The low rate of linkage dis- simple funnel breeding design (Fig. 1; Huang et al. 2015). equilibrium decay within chromosomes. There are normally This is however not essential, for example, the first MAGIC only one or two recombinants per chromosome arm population in plants used 19 A. thaliana parents (Kover (inbreeding a RIL only adds about one observable recom- et al. 2009). Each MAGIC line usually inherits alleles from binant per arm) meaning only a few hundred genotyped all parents, and MAGIC chromosomes are random mosaics markers are needed to map QTL. of the founder haplotypes. By capturing increased genetic However, bi-parental populations have two principal dis- recombination and genetic variation, MAGIC populations advantages: the lack of mapping precision, which stems from are designed to address both of the principal limitations of limited effective recombination occurring during population bi-parental populations for QTL mapping. development, and low genetic diversity, which is due to the The beneficial properties of MPPs, namely high mapping genetic bottleneck caused by the choice of two founders. This power and resolution, expanded diversity compared with bi- may limit the number of QTL captured as no more than two parental populations, and their minimal population structure alleles segregate at any locus. Consequently, around a decade has increased their uptake in crop research. This increasing ago, a second generation of experimental mapping popula- popularity of crop MPPs means that many now represent tions, initially utilising additional crossing generations in a bi- mature research and development tools. Most of the world’s parental but eventually inter-crossing multiple parents major crops have spawned several MPPs (Table 1) and new (MPPs), was developed to address these issues. MPPs for other crops are imminent (e.g., pigeonpea, The limited genetic recombination in bi-parental popu- Cajanus cajan and chickpea, Cicer arietinum, MAGIC lations was first addressed via the advanced inter-cross populations with whole-genome sequence data, Pandey (AIC) design. These capture additional recombination via et al. 2016; Roorkiwal et al. 2020) or under development crossing the F2 generation for further generations